Biometric Authentication and Robot Access Control for Secure Health Devices

Abstract

Medical devices and healthcare robots are increasingly networked, making robust authentication and fine-grained access control essential to patient safety, privacy, and regulatory compliance. This article provides an extended, interdisciplinary review of biometric authentication modalities and access-control mechanisms for robotic and Internet-of-Medical-Things (IoMT) devices, synthesizes the threat landscape, and proposes a layered, privacy-preserving framework for biometric-enabled robot access control (BERAC) suitable for clinical deployments. We examine physiological and behavioral biometrics (fingerprint, face, iris, electrocardiogram/photoplethysmography, gait, keystroke), continuous and adaptive authentication, cryptographic and hardware protections, role- and context-aware access control models for robots, and system-level considerations including latency, survivability, fail-safe behavior, and regulatory compliance (NIST, FDA). We conclude with privacy, ethical, and implementation guidelines for designers, vendors, and hospitals.